Build In-Demand Data Science and AI Skills

 Introduction to Data Science and AI

Begin your learning journey with foundational concepts in data, Python programming, and Generative AI. This is a pre module to prepare you for the advanced modules on Data Science and AI, reinforcing essential mathematical and statistical principles needed for the weeks ahead. 

• Introduction to the World of Data 
• Introduction to Python 
• Introduction to Generative AI 
• Applications of Data Science and AI 
• Data Science Lifecycle 
• Mathematics and Statistics behind Data Science and AI 
• History of Data Science and AI

Foundations of AI 

In this Generative AI masterclass taken by experts, you will explore the use cases of Generative AI. Learn practical techniques to integrate GenAI into your data workflows.

Making Sense of Unstructured Data

• Clustering

• Dimensionality Reduction techniques (PCA, t-SNE)

This week, you will be involved in a hands-on project focused on clustering and PCA techniques. Attend a specialized Generative AI masterclass on learning from Text Data. 

•  Project on Clustering and PCA 
• Masterclass on Learning from Text Data

• Introduction to Supervised Learning and Regression

• Model Evaluation, Cross-Validation, and Bootstrapping

• Introduction to Classification
• Hypothesis Testing
• Logistic Regression
• Decision Trees and Random Forest

This week, you will be involved in a project where you will apply your understanding of machine learning classification. Attend a masterclass on AI-powered text labeling that covers its practical implementation using Generative AI techniques.

•  Project on Machine Learning Classification 
• Masterclass on AI-Powered Text Labeling

This week, you will explore the fundamentals of Deep Learning, the concept of neurons and Artificial Neural Networks (ANNs) function. This module will also introduce you to Computer Vision and CNN Architecture and Transfer Learning.

• Introduction to Deep Learning 
• The Concept of Neurons 
• Artificial Neural Networks (ANNs) 
• Introduction to Computer Vision 
• CNN Architecture and Transfer Learning

• Recommendation Systems 
• Recommendation Systems - Clustering, Collaborative Filtering & SVD

This week will introduce you to the ethical implications of AI by exploring concepts such as bias, causality, and privacy. Learn about the AI lifecycle, feedback loops, and interdependencies to ensure responsible and fair AI system development and deployment.

•  Introduction to AI Lifecycle 
• Introduction to Bias and Its Examples 
•  Introduction to Causality and Privacy 
• Interconnections and Domains 
•  Interdependency and Feedback in AI Systems

This week, you will involved in a project based on Recommendation Systems using real-world data. 

•  Project on Recommendation System